Application of artificial neural network to the prediction of Pb-Al composite properties

The third component´s ingredient which is between the Pb and the Al and the hot dipping temperature has the major impact on the physical property of the Pb-Al composite. Therefore if needs to change the ingredient of the third component and the hot dipping temperature in the preparation process, then measure the related indicators of its physical proper to find out the optimum combination. It is complex and consumes more manpower and resources. This article constructs neural network model using the limited data, and predict the optimum combination of the ingredient of the third component and the hot dipping temperature. The prediction results can be used for a reference in instructing the further experimental design.